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C. Hennig

30 papers hereh-index 406.2k citations147 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author9
  • first author3
  • middle author6
  • last author11

Across the 29 of 30 papers where every author was matched, so the position is known.

fields
  • stat.ME16
  • stat.OT6
  • stat.ML3
  • math.ST2
  • stat.AP2
  • econ.EM1
same name
  • C. Hennig — 12 papers, h 11
  • C. Hennig — 3 papers, h 3
  • C. Hennig — 1 paper, h 46

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20042023
most citedRecovering the number of clusters in data sets with noise features using feature rescaling factors

362 citations · 612 across the 28 of their papers we have counts for

collaborators
Showing 2015Show all

4 papers · 1 filter

stat.OT2015★ 4 cited

Beyond subjective and objective in statistics

Andrew Gelman, Christian Hennig

We argue that the words "objectivity" and "subjectivity" in statistics discourse are used in a mostly unhelpful way, and we propose to replace each of them with broader collections…

stat.ME2015★ 2 cited

Clustering strategy and method selection

Christian Hennig

This paper is a chapter in the forthcoming Handbook of Cluster Analysis, Hennig et al. (2015). For definitions of basic clustering methods and some further methodology, other chapt…

stat.ME2015

Flexible parametric bootstrap for testing homogeneity against clustering and assessing the number of clusters

Christian Hennig, Chien-Ju Lin

There are two notoriously hard problems in cluster analysis, estimating the number of clusters, and checking whether the population to be clustered is not actually homogeneous. Giv…

stat.OT2015★ 3 cited

What are the true clusters?

Christian Hennig

Constructivist philosophy and Hasok Chang's active scientific realism are used to argue that the idea of "truth" in cluster analysis depends on the context and the clustering aims.…

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